This research seeks to reduce the uncertainties in estimating acoustic velocities, a property of the subsurface playing a key role in the quality of seismic images. Our approach is a variant of Full Waveform Inversion (FWI). This technique iteratively modifies a velocity model towards one that fits the data best. It is effective in predicting short wavelength reflectivity in seismic data, but often fails to update long wavelength component. The resulting model often represents a local minimum in the solution space, and does not correctly describe Earth structure. We employ extended models, with additional parameters beyond location in the subsurface, which serve to relax the FWI problem and make its global minimum easier to attain. Previous research has suggested that this extended FWI (EFWI) can recover long wavelength component of a velocity model. This research extends earlier work using synthetic data to field OBS node and streamer data in the plane wave domain. The methods under development use existing data acquisition modes and public domain software to provide a global solution for FWI, thus adding to the growing number of solutions to tackle one of the greatest challenges facing velocity estimation today.
